Microsoft ML.Net Machine Learning for .Net Developers Using C#.Net (en Inglés)
Reseña del libro "Microsoft ML.Net Machine Learning for .Net Developers Using C#.Net (en Inglés)"
Machine Learning has become a fundamental and integral part of many novel business solutions. Until now, those with C#.NET Programming experience had to learn either R or Python to delve into the Machine Learning world. Fortunately, Microsoft has recently released ML.NET (version 1.2) Machine Learning package. C# .NET Programmers worldwide can now leverage their C#.NET experience to train, evaluate and build Machine Learning Models and solutions using Microsoft ML.NET package. Microsoft ML.NET package, available for download from https: //www.nuget.org, is an excellent collection of Machine Learning Algorithms covering a wide range of Machine Learning Tasks including Text Classification, Binary and Multi-class Classification, Regression, Cluster Analysis, Recommender, among others, And all of these algorithms can now be used for training, evaluating and using Machine Learning Models in C#.NET. Now, C#.NET Programmers can develop novel and intelligent Apps for Windows Desktop using their extensive C#.NET experience. Those who prefer to use Xamarin to develop cross-platform Apps for Android or IOS or MacOS using C#.Net can now incorporate Machine Learning Models directly in their Apps leveraging their C#.NET experience. Those who develop, using Unity 3D, games or Data Visualization applications can now incorporate Machine Learning Models in their games or applications using C#.NET. The possibilities are limited only by your imagination. In the 'Microsoft ML.NET Machine Learning for .NET Developers using C#.NET' book (Volume I), you will find C#.NET Programs that take you step-by-step in completing Machine Learning Model training, evaluation and use for specific tasks and algorithms. Along with step-by-step discussion of the C# Program for each Algorithm covered in the book, you will also find Demonstration Videos for each Chapter covering each Algorithm and showing what to do at each step. The book also provides full code-listing with comments for each Chapter. Additionally, you will be able to download the Chapter example and sample C#.NET programs from the Github repository for this book. This book assumes that you are familiar with Visual Studio 2019 and that you are somewhat comfortable with C#.NET Programming language at a fundamental level.With this book, you will learn: *To download and import Microsoft ML.NET package directly into your Visual Studio 2019 Solution*To add Training and Testing Data Sets to your Visual Studio 2019 Solution*To add and create C# classes that serve as Input and Output Data Model classes for your Machine Learning Model*To work with specific Algorithms for Binary Classification and Multi-class Classification*To perform Sentiment Analysis and Iris Flower Classification*To use and apply MLContext and IDataView objects in developing Machine Learning Models*To Evaluate Machine Learning Models using various Performance Metrics*To use and apply Trained Machine Learning Models for Prediction or Classification Tasks*To save Trained Machine Learning Models for application development at a later date*To create a Sentiment Analysis Windows .NET App that uses already trained Machine Learning Model
